class_docstr: Base class for defining classification loss functions. Sub-classes must implement forward function.
  
  Args:
      opts: command line arguments
docstr: Add criterion-specific arguments to the parser.
docstr_tok: ["Add","criterion-specific","arguments","to","the","parser","."]
code: def add_arguments(
      cls, parser: argparse.ArgumentParser
  ) -> argparse.ArgumentParser:
      """Add criterion-specific arguments to the parser."""
      if cls != BaseClassificationCriteria:
          # Don't re-register arguments in subclasses that don't override `add_arguments()`.
          return parser
  
      group = parser.add_argument_group(cls.__name__)
      group.add_argument(
          "--loss.classification.name",
          type=str,
          default=None,
          help=f"Name of the loss function in {cls.__name__}. Defaults to None.",
      )
      return parser
  
file_path: ml-cvnets/loss_fn/classification/base_classification_criteria.py
imports: import argparse
  from typing import Any, Dict, Union
  from torch import Tensor
  from loss_fn import LOSS_REGISTRY, BaseCriteria
  from utils import logger
label_desc: Use image node_id 2 for calling the BaseClassificationCriteria obj's underlying member method code with example usage: obj.add_arguments(cls, parser) and returns: parser, parser